Development and Validation of Software for Modeling Vagus Nerve Stimulation Across Species

Limited Access
This item is unavailable until:
2025-05-24

Date

2023

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats

47
views
0
downloads

Abstract

Electrical stimulation and block of peripheral nerves hold great promise for treatment of a range of disease and disorders, but promising results from preclinical studies often fail to translate to successful clinical therapies. Differences in neural anatomy across species require different electrodes and stimulation parameters to achieve equivalent nerve responses, and accounting for the consequences of these factors is difficult. In Chapter 2, we describe the implementation, validation, and application of a standardized, modular, and scalable computational modeling pipeline for biophysical simulations of electrical activation and block of nerve fibers within peripheral nerves. The ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds) pipeline provides a suite of built-in capabilities for user control over the entire workflow, including libraries for parts to assemble electrodes, electrical properties of biological materials, previously published fiber models, and common stimulation waveforms. We validated the accuracy of ASCENT calculations, verified usability in beta release, and provide several compelling examples of ASCENT-implemented models. ASCENT will enable the reproducibility of simulation data, and it will be used as a component of integrated simulations with other models (e.g., organ system models), to interpret experimental results, and to design experimental and clinical interventions for the advancement of peripheral nerve stimulation therapies.

Next, in Chapter 3 we demonstrated how ASCENT can be applied to simulate accurately nerve responses to electrical stimulation. We simulated vagus nerve stimulation (VNS) for humans, pigs, and rats. We informed our models using histology from sample-specific or representative nerves, device design features (i.e., cuff, waveform), published material and tissue conductivities, and realistic fiber models. Despite large differences in nerve size, cuff geometry, and stimulation waveform, the models predicted accurate activation thresholds across species and myelinated fiber types. However, our C fiber model thresholds overestimated thresholds across pulse widths, suggesting that improved models of unmyelinated nerve fibers are needed. Our models of human VNS yielded accurate thresholds to activate laryngeal motor fibers and captured the inter-individual variability for both acute and chronic implants. For B fibers, our small-diameter fiber model underestimated threshold and saturation for pulse widths >0.25 ms. Our models of pig VNS consistently captured the range of in vivo thresholds across all measured nerve and physiological responses (i.e., heart rate, Aδ/B fibers, Aγ fibers, EMG, and Aα fibers). In rats, our smallest diameter myelinated fibers accurately predicted fast fiber thresholds across short and intermediate pulse widths; slow unmyelinated fiber thresholds overestimated thresholds across shorter pulse widths, but there was overlap for pulse widths >0.3 ms. We elevated standards for models of peripheral nerve stimulation in populations of models across species, which enabled us to model accurately nerve responses, demonstrate that individual-specific differences in nerve morphology produce variability in neural and physiological responses, and predict mechanisms of VNS therapy and side effect.

Lastly, in Chapter 4 we investigated how previous efforts to translate VNS therapies (e.g., for stroke, heart failure, and rheumatoid arthritis) have not accounted for individual and species-specific differences in nerve responses while selecting stimulation parameters, which could explain why clinical outcomes have not reproduced promising results from preclinical animal studies. We used previously validated computational models of VNS based on individual-specific nerve morphologies for populations of rats, pigs, and humans from Chapter 3 to show that a range of thresholds exists to achieve a target nerve response within and across species. We found that applying the same parameters across individuals of a species and recycling or linear scaling of stimulation parameters across species produces a large range of nerve responses. Our work highlights the need for systematic approaches to select stimulation parameters that account for individual- and species-specific differences in nerve responses to stimulation, which may be required to achieve higher response rates and greater therapeutic benefit from VNS therapies.

Description

Provenance

Citation

Citation

Musselman, Eric David (2023). Development and Validation of Software for Modeling Vagus Nerve Stimulation Across Species. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/27755.

Collections


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.